Computing, Analytics, and Modeling
PeakQC Software Advances Quality Control for Omics-Agnostic Mass Spectrometry
Novel software tool enables quality control independent of omics molecular types and can be used on multiple platforms.
A team of researchers developed PeakQC, a new software tool for robust quality control of mass spectrometry data. (Image courtesy of iStock | aurielaki)
The Science
Quality control (QC) strategies for monitoring and assessing instrument performance during mass spectrometry analysis is crucial to make sure that the data generated is high-quality, reproducible, and accurate. Particularly for metabolomics and lipidomics, traditional QC approaches often involve manual inspection of the data, which is time-consuming, subjective, prone to human error, and unviable for high-throughput studies with hundreds of samples. A team of scientists from across Pacific Northwest National Laboratory (PNNL) and the Environmental Molecular Sciences Laboratory, a Department of Energy Office of Science user facility at PNNL, have developed PeakQC, a new software tool for automated quality control of mass spectrometry data. Unlike existing QC tools that focus on specific types of molecules, PeakQC can analyze data from various “omics” fields, like proteomics, metabolomics, and lipidomics. The software performs global and detailed QC assessments and works with different instruments and experimental setups, including liquid chromatography and ion mobility spectrometry.
The Impact
PeakQC addresses a critical need in the growing field of mass spectrometry-based omics research. By providing automated QC that works across different types of molecules and experimental setups, this new software can help researchers maintain data reliability and catch problems early. This could lead to more efficient use of resources, better reproducibility in experiments, and ultimately more trustworthy scientific conclusions. The tool's flexibility makes it particularly valuable as more studies combine multiple “omics” approaches. PeakQC enables the collection of high-quality data in large-scale user projects at EMSL and within PNNL. The tool not only enables comparison of outputs from multiple mass spectrometry approaches, but also facilitates the collection of reproducible data.
Summary
A team of researchers at EMSL and PNNL recently developed PeakQC, a software program that uses advanced algorithms and machine learning to provide rapid and unbiased assessment of mass spectrometry data quality. It can analyze data from various instrument types and experimental methods, including both data-dependent and data-independent acquisition modes. The software is a desktop and stand-alone tool that generates diagnostic plots and metrics without relying on other molecular identification tools, which are often complicated to set up and use. It is freely available, easy to use, and requires no installation. Once downloaded, users can launch the tool on their own device.
PeakQC can use either user-specified ions or automatically detected ions to extract quality control metrics. This approach allows it to pinpoint specific causes of performance issues, unlike some existing tools that only provide general quality assessments. By offering a unified approach to quality control across different “omics” fields, PeakQC represents a significant advancement in mass spectrometry data analysis. Its development highlights the growing importance of robust, automated quality control in large-scale scientific studies using mass spectrometry.
Contact
Aivett Bilbao, EMSL, Aivett.bilbao@pnnl.gov
Funding
Portions of this work were supported by a grant from the National Cancer Institute’s Clinical Proteomic Tumor Analysis Consortium; the Agile BioFoundry, supported by the Department of Energy, Energy Efficiency and Renewable Energy, Bioenergy Technologies Office; EMSL; and the DOE Office of Science, Office of Workforce Development for Teachers and Scientists under the Science Undergraduate Laboratory Internships and Community College Internships programs.
Publication
A. Harrison, et al. 2024. “PeakQC: A Software Tool for Omics-Agnostic Automated Quality Control of Mass Spectrometry Data.” Journal of the American Society for Mass Spectrometry. [DOI: 10.1021/jasms.4c00146]
This article is part of the 2024 Emerging Investigators Special Issue highlighting EMSL computational scientist Aivett Bilbao’s research leading advances in computational mass spectrometry and artificial intelligence/machine learning.